Practical AI on the Microsoft stack. Azure OpenAI, Microsoft 365 Copilot, Power Platform AI Builder — configured for your workflow, hosted in Australia, with the audit-trail compliance-heavy sectors actually need. Less AI hype, more AI that ships.
We're a Microsoft partner. Our AI work runs on Microsoft AI services (Azure OpenAI, Copilot, Power Platform AI Builder) and stays inside your Microsoft tenant. That keeps the security, identity, and audit-trail story consistent with the rest of your stack.
Azure OpenAI deployed to Australia East / Southeast. Your data and prompts stay in Australian datacentres. Not used for model training.
We default to AI assistance, not AI autonomy. AI proposes, humans approve. Important in regulated sectors where automated decisions create real exposure.
Every AI interaction logged: prompt, response, staff member, timestamp. Defensible under ACNC, Aged Care Act 2025, DEX, and NDIS audit.
Same security model, same identity, same compliance posture as the rest of your Microsoft stack. No third-party AI vendor relationships to govern separately.
Four practical AI workstreams. Most engagements combine two or three based on what your organisation actually needs.
Embed GPT-4 class models into your existing line-of-business systems — Dynamics 365, SharePoint, custom apps. Document summarisation, intelligent search, drafting assistance, classification — configured for your workflow and data.
The licensing, governance, and change-management work that turns Copilot from "a thing we paid for" into a thing your staff actually use. Includes data-readiness audit, SharePoint permissions cleanup, and role-specific training.
Pre-built AI components dropped into Power Apps and Power Automate — form processing, document extraction, sentiment analysis, prediction models. Lower-risk AI for workflows that don't need a custom build.
Sector-specific AI workflows where the off-the-shelf tools don't fit. Our MACS-AI voice agent (aged care) and MNFP intake assistant (NFP) are examples — we can build similar for your sector.
We've productised our AI work for three Australian sectors where the privacy, compliance, and audit-trail constraints are most demanding — useful as reference architectures.
Pre-clinical AI for Australian aged-care providers: voice agent for after-hours enquiries, smart enquiry form, document ingestion. Aged Care Act 2025-compatible audit trail.
See MACS-AIPractical AI for Australian NFPs: enquiry triage, case-note summarisation, follow-up suggestion. DEX, ACNC, NDIS-defensible.
See MNFP-AIAI for Australian NDIS-registered providers: voice-agent intake for after-hours referrals, smart enquiry form, document ingestion for plans and assessments. Practice Standards-defensible audit trail.
See MDS-AIGovernment, professional services, membership organisations — we'll scope an AI workstream that matches your compliance environment and your existing Microsoft licensing.
Discuss your sectorWhat we will and won't do with your data when AI is involved.
All AI inference runs in Australian Azure regions, defaulting to Australia East (Sydney).
Your data is not used to train Microsoft's or OpenAI's models, per Azure OpenAI commercial terms.
Prompt and completion logs are retained according to your policy, not Microsoft's default.
We don't use third-party AI APIs for client work without your explicit sign-off.
Consent capture and audit trails are designed in from the start, not bolted on at the end.
Common questions from Australian organisations weighing up an AI workstream on the Microsoft stack.
We start with a short discovery on your existing Microsoft estate, your compliance environment and the workflows that are currently manual or slow. From that we scope one narrow workstream rather than a platform-wide programme.
The first deliverable is usually a working slice in your own tenant that you can test with real staff, not a slide deck.
Inference runs in Australian Azure regions, defaulting to Australia East (Sydney). Your prompts and completions are not used to train Microsoft's or OpenAI's models, per Azure OpenAI commercial terms.
Log retention follows your policy rather than a vendor default, and we stay Microsoft-stack unless you explicitly sign off on something else.
Not necessarily. A lot of the useful work sits in Azure OpenAI and Power Platform rather than Microsoft 365 Copilot, and those are licensed separately.
Part of discovery is working out what your existing licensing already covers, so you're not buying seats you don't need yet.
Yes. Most of our AI work lands on top of a Dynamics 365 or Power Platform environment that already exists, including ones we didn't build.
If the underlying data model is the real constraint, we'll say so before proposing an AI layer on top of it.
The reliable wins are upstream of clinical or statutory decisions: triaging inbound enquiries, drafting and summarising notes for a human to approve, extracting structured fields from documents, and suggesting follow-ups.
We don't position AI as making regulated decisions. A person stays in the loop, and the audit trail records what was suggested and who approved it.
Outputs are treated as drafts. The workflow captures what the model proposed, what the human changed, and who signed off, so the record stands up under audit.
Where a task can't tolerate a wrong answer, we'd rather scope it out than paper over it with a confidence score.
That's a normal outcome of discovery. Some of the workflows people ask us to apply AI to are better fixed with a form, an integration or a process change.
We'll tell you which parts aren't worth an AI spend, and you're free to take that away and act on it yourself.
Book a 30-minute conversation. We'll look at your current Microsoft estate, your compliance constraints, and the workflows where AI is most likely to pay back — and tell you honestly which ones aren't worth it.
